The emerging threat of drug resistant bacteria in hospitals is one of the most pressing pandemics clinicians are currently facing. A recent study of cardiac ICUs found that 75% of Staphylococcus aureus and 95% of coagulase-negative staphylococci were identified as methicillin resistant. The beta-lactam class of antibiotics (e.g. penicillins, cephalosporins) work by disrupting the activity of bacterial transpeptidases which are largely responsible for creating bacterial cell walls. To combat these drugs bacteria employ beta-lactamases, which are their most common defense against antibiotics. In response to this problem inhibitors are added to commercially available antibiotics which bind and depress beta-lactamase activity. The long term goals of this work are to assist in the development and understanding of beta-lactam based antibiotics and inhibitors. This can be accomplished by better understanding the underlying mechanisms that govern drug resistance and proposing ways to exploit this information. I hypothesize that the development and application of novel computational methods can evaluate the effectiveness of current drug development strategies. Specifically, should new antibiotics be targeted toward better binding in peptidases or should an alternative strategy be employed? Our initial aim is to develop and validate novel methods for calculating the free energies of protein assisted chemical reactions. Upon completion we will employ these methods to determine whether future beta-lactam based antibiotics should be targeted toward greater binding affinity in native bacterial peptidases or whether it is more advantageous to design drugs that preferentially stabilize protein based chemical reactions. Our final aim will involve computing the free energy of native and mutant beta-lactamase states and examining mechanisms by which these proteins sustain the ability to break down antibiotics while repressing inhibitor activity. Completion of these aims will result in an improved description of drug resistance mechanisms and will allow researchers to exploit this information in the creation of new antibiotics and inhibitors. The funding from this grant will support the my career development via additional training (e.g. courses, advisement, presentations, grant writing, research). In addition, I plan to take advantage of the teaching opportunities at NIH which will give a unique boost to my desire to transition into an independent assistant professor position. (End of Abstract)